Contents
lists
available
at
Seminars
in
Cell
&
Developmental
Biology
j
o u r n a
l
h
o
m e
p a g e :
w w w . e l s e v i e r . c o m / l o c a t e / s e m c d b
Review
Planarian
regeneration
as
a
model
of
anatomical
homeostasis:
Recent
progress
in
biophysical
and
computational
approaches
Michael
Levin a,b,∗,
Alexis
M.
Pietak a,
Johanna
Bischof a,b
a Allen
Discovery
Center
at
Tufts
University,
Medford,
MA
02155,
United
States
b Biology
Department,
Tufts
University,
Medford,
MA
02155,
United
States
a
r
t
i
c
l
e
i
n
f
o
Article
history:
Received
5
January
2018
Received
in
revised
form
3
April
2018
Accepted
6
April
2018
Available
online
1
May
2018
Keywords:
Planaria
Dugesia
japonica
Regeneration
Patterning
Morphostasis
a
b
s
t
r
a
c
t
Planarian
behavior,
physiology,
and
pattern
control
offer
profound
lessons
for
regenerative
medicine,
evolutionary
biology,
morphogenetic
engineering,
robotics,
and
unconventional
computation.
Despite
recent
advances
in
the
molecular
genetics
of
stem
cell
differentiation,
this
model
organism’s
remark-
able
anatomical
homeostasis
provokes
us
with
truly
fundamental
puzzles
about
the
origin
of
large-scale
shape
and
its
relationship
to
the
genome.
In
this
review
article,
we
first
highlight
several
deep
mysteries
about
planarian
regeneration
in
the
context
of
the
current
paradigm
in
this
field.
We
then
review
recent
progress
in
understanding
of
the
physiological
control
of
an
endogenous,
bioelectric
pattern
memory
that
guides
regeneration,
and
how
modulating
this
memory
can
permanently
alter
the
flatworm’s
target
morphology.
Finally,
we
focus
on
computational
approaches
that
complement
reductive
pathway
analy-
sis
with
synthetic,
systems-level
understanding
of
morphological
decision-making.
We
analyze
existing
models
of
planarian
pattern
control
and
highlight
recent
successes
and
remaining
knowledge
gaps
in
this
interdisciplinary
frontier
field.
©
2018
Elsevier
Ltd.
All
rights
reserved.
Contents
1.
Introduction
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126
1.1.
A
primer
on
planarians’
functional
features
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126
1.2.
Fundamental
knowledge
gaps .
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126
1.3.
Perspective
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128
2.
Physiological
controls
of
patterning .
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. 128
2.1.
Prediction
1:
ion
channels
and
voltage
gradients
are
involved
in
planarian
patterning
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128
2.2.
Prediction
2:
neurotransmitters
are
involved
in
planarian
patterning
control
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130
2.3.
Prediction
3:
anatomical
outcome
and
genetic
default
can
diverge
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130
2.4.
Prediction
4:
pattern
memory
can
be
over-written
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133
2.5.
Summary:
physiological
controls
of
growth
and
form
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134
3.
Computational
approaches
to
an
integrative
understanding
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134
3.1.
Current
state
of
the
art
in
understanding
regenerative
dynamics:
gradients
and
beyond
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135
3.2.
Advances
in
modeling
and
simulation:
testing
available
models
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3.3.
Tools
for
model
discovery
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137
4.
Conclusion
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138
Acknowledgements
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138
References
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138
∗ Corresponding
author
at:
Allen
Discovery
Center
at
Tufts
University,
200
College
Avenue,
Medford,
MA
02155,
United
States.
address:
(M.
Levin).
https://doi.org/10.1016/j.semcdb.2018.04.003
1084-9521/©
2018
Elsevier
Ltd.
All
rights
reserved.